
# Load raw data
from scipy.io import loadmat
betaIn = loadmat('betasMF_Astate.mat')
thetaIn = loadmat('theta.mat')

# Convert to Xarray
import numpy as np
import epsproc as ep
from epsproc.sphCalc import setBLMs

# BLM = setBLMs(betaIn['beta'], dimNames=['BLM','tPol'], t=np.linspace(0,np.pi,100).round(3), tUnits='Rad')   # v1
BLM = setBLMs(betaIn['beta'], dimNames=['BLM','tPol'], t=thetaIn['theta'].squeeze().round(3), tUnits='Rad')   # v2 with theta

OMP: Info #276: omp_set_nested routine deprecated, please use omp_set_max_active_levels instead.

* sparse not found, sparse matrix forms not available. 
* natsort not found, some sorting functions not available.

* Setting plotter defaults with epsproc.basicPlotters.setPlotters(). Run directly to modify, or change options in local env.

* Set Holoviews with bokeh.
* pyevtk not found, VTK export not available.


# Add conjugate pairs (L,-M)
# Note existing function uses Yl,m = conj((-1)^m * Yl,-m)
# Cf. VM conj: beta_{LM} = (-1)^(L - M) * beta_{L-M}, but doesn't matter in this case.
from epsproc.sphFuncs import sphConv
BLMconj = sphConv.sphConj(BLM)

# Merge data
# BLMfull = BLM + BLMconj.where(BLMconj.m<0)
# BLMfull
BLMfull = BLM.combine_first(BLMconj.where(BLMconj.m<0))
# BLMconj.where(BLMconj.m<0)

BLMfull = sphConv.cleanLMcoords(BLMfull)

from epsproc.util.conversion import renormL0
BLMfullNorm = renormL0(BLMfull)


# Check BLMs - plot looks OK, aside from added terms with M>L!  Issue with unstack here...

# Set some plot options
imgWidth = 1000
imgHeight = 600
ep.plot.hvPlotters.setPlotters(width=imgWidth, height=imgHeight)
plotBackend='hv'

# Plot - unnorm
# ep.BLMplot(BLMfull, xDim='tPol', backend=plotBackend, thres=0.1)

# ep.BLMplot(sphConv.cleanLMcoords(BLMfull.unstack()), xDim='tPol', backend=plotBackend)

# Plot - renorm
ep.BLMplot(BLMfullNorm, xDim='tPol', backend=plotBackend, thres=0.1)

* Set Holoviews with bokeh.


# Plot some PADs from BLMs
# Set the backend to 'pl' for an interactive surface plot with Plotly

# Explict row,column layout setting for figure
rc = [3,5]  

# Compute expansions from BLM parameters and return figure objext
plotBackend='pl'
dataPlot, figObj = ep.sphFromBLMPlot(BLMfullNorm.sel(tPol=slice(0,np.pi,8)), facetDim='tPol', backend = plotBackend, rc=rc,     #, returnFlag=True);
                                    plotFlag=True,height=1000, width=1200)
# figObj[0]

Using complex betas (from BLMX array).
*** WARNING: plot dataset has min value < 0, min = (-0.743125240391105+0j). This may be unphysical and/or result in plotting issues.
Sph plots: 
Plotting with facetDims=tPol, pType=a with backend=pl.
*** Plotting for [1,1,0]
*** Plotting for [1,2,1]
*** Plotting for [1,3,2]
*** Plotting for [1,4,3]
*** Plotting for [1,5,4]
*** Plotting for [2,1,5]
*** Plotting for [2,2,6]
*** Plotting for [2,3,7]
*** Plotting for [2,4,8]
*** Plotting for [2,5,9]
*** Plotting for [3,1,10]
*** Plotting for [3,2,11]
*** Plotting for [3,3,12]
*** Plotting for [3,4,13]
*** Plotting for [3,5,13]


# # Try class version, better plotter...
# plotBackend='pl'

# # Explict row,column layout setting for figure
# rc = [3,5]  

# # Example using data class 
# from pemtk.fit.fitClass import pemtkFit
# data = pemtkFit()


#  # Set data in class, and plot PADs
# data.setData('X', BLMfullNorm)
# data.padPlot(keys = 'X', dataType='AFBLM', Etype='tPol', selDims={'tPol':slice(0,np.pi,8)}, backend=plotBackend,
#               rc = rc, height=1000, width=1200)  

# data.BLMplot(keys = 'X', Etype='tPol', xDim='tPol', backend='hv')


import scooby
scooby.Report(additional=['epsproc', 'holoviews', 'hvplot', 'xarray', 'matplotlib', 'bokeh'])


# Check current Git commit for local ePSproc version
from pathlib import Path
!git -C {Path(ep.__file__).parent} branch
!git -C {Path(ep.__file__).parent} log --format="%H" -n 1

* 3d-AFPAD-dev
  dev
  master
38f0b8a210146743906c7ef19f508d9035d096fd


# Check current remote commits
!git ls-remote --heads https://github.com/phockett/ePSproc

8c9201fdcb98f42875730b94282f50328decab8a	refs/heads/3d-AFPAD-dev
7e4270370d66df44c334675ac487c87d702408da	refs/heads/dev
1c0b8fd409648f07c85f4f20628b5ea7627e0c4e	refs/heads/master
69cd89ce5bc0ad6d465a4bd8df6fba15d3fd1aee	refs/heads/numba-tests
ea30878c842f09d525fbf39fa269fa2302a13b57	refs/heads/revert-9-master
baf0be0c962e8ab3c3df57c8f70f0e939f99cbd7	refs/heads/testDev

Wed Aug 21 11:55:26 2024 EDT
OS	Linux	CPU(s)	64	Machine	x86_64	Architecture	64bit
RAM	62.8 GiB	Environment	Jupyter	File system	btrfs
Python 3.10.11 \| packaged by conda-forge \| (main, May 10 2023, 18:58:44) [GCC 11.3.0]
epsproc	1.3.2-dev	holoviews	1.16.2	hvplot	0.8.4	xarray	2022.3.0
matplotlib	3.5.3	bokeh	3.1.1	numpy	1.23.5	scipy	1.10.1
IPython	8.13.2	scooby	0.7.2

ELI CO2 - MF-PAD plots from VM's matrix recon¶

Read data¶

Quick plots¶

$\beta_{L,M}$¶

MF-PADs¶

Versions¶